农村数字化发展能否提升林业经济韧性——基于30个省域面板数据的实证检验

doi:10.11707/j.1001-7488.LYKX20230484

Abstract

Abstract:

Objective: This study aims to investigate the mechanisms through which rural digital development improves forestry economic resilience, providing a scientific basis for promoting the formation of a new pattern of sustainable forestry development. Method: Drawing upon panel data from 30 provinces (autonomous regions, municipalities) in China spanning the period 2011 to 2020, we constructed quantified measures of rural digital development and an evaluation index system for forestry economic resilience. Employing various statistical models including fixed effect, mechanism testing, panel threshold effect and spatial Dubin models, we analyzed the relationship between rural digital development and forestry economic resilience. Result: 1) Rural digital development is found to positively influence forestry economic resilience by enhancing productivity in both labor and land factors. These results remains robust even after a series of robustness tests and endogenous treatments. Significant regional differences exist in the impact of rural digital development, with stronger effects observed in the eastern region of China. Moreover, the enhancing effect of rural digital development on forestry economic resilience strengthens as the resilience level increases. 2) The relationship between rural digital development and forestry economic resilience exhibits nonlinear characteristics, characterized by an initial strong“digital dividend”, followed by a“digital bottleneck”in the middle stage, and ultimately yielding increasing benefits in the later stage. 3) There is a threshold effect of rural digital development on forestry economic resilience. When the level of digital development is below the first threshold, the impact on forestry economic resilience is significantly positive. However, as the level of digital development increases beyond the first threshold, the marginal returns diminish. Significant spatial spillover effects between rural digital development and forestry economic resilience are identified, with both direct and indirect effects being positive. 4) In addition to the level of rural digital development, economic development, industrial structure, and precipitation also wield significant positive effects on forestry economic resilience. Conclusion: Rural digital development stands as a potent means to effectively enhance forestry economic resilience. Accordingly, we advocate for leveraging digital technology to optimize labor and land resource allocation, fostering robust growth in the rural digital economy, and enhancing forestry economic resilience through phased, dynamic, and differentiated strategies. Concurrently, efforts to fortify economic support, streamline industrial structures, and leverage natural endowments should be intensified to further bolster forestry economic resilience.

Key words: rural digital development, forestry economic resilience, resource allocation efficiency, digital dividend

CLC Number:

S7-9
F326.24

Yali Mu,Hao Wang,Hongqiang Yang,Fanbin Kong. Can the Rural Digital Development Improve Forestry Economic Resilience: An Empirical Evidence Based on Panel Data of 30 Provinces[J]. Scientia Silvae Sinicae, 2024, 60(5): 51-66.

Figures/Tables 17

Fig.1

Table 1

Table 2

Comprehensive evaluation system for the level of rural digital development"

一级指标 Primary indicators	二级指标 Secondary indicators	三级指标 Tertiary indicators	属性 Attribute
数字基础设施 Digital infrastructure	农村互联网普及率 Rural Internet penetration rate	开通互联网宽带业务的行政村比重 Proportion of administrative villages with internet broadband service activated	+
	农村互联网普及率 Rural Internet penetration rate	农村宽带接入用户/乡村户数 Rural broadband access subscribers/rural households	+
	农村信息化设备 Rural information technology equipment	农村居民每百户计算机拥有量 Number of computers per 100 rural households	+
		农村居民每百户移动电话拥有量 Cell phone ownership per 100 rural households	+
		农村居民每百户彩色电视机拥有量 Color television sets per 100 rural households	+
	农村气象观测业务 Rural meteorological observation operations	农业气象观测站 Agricultural meteorological observation station	+
数字服务水平 Digital service level	农村信息技术应用 Rural IT applications	农村营业网点服务人口 Population served by rural business outlets	?
	农村数字产品与服务消费 consumption of rural digital products and services	农村居民数字产品及服务的消费支出 Expenditure on digital products and services of rural residents	+
	农村数字金融 Rural digital finance	数字普惠金融水平（指数） Digital inclusive finance level (index)	+
	农村生产投资 Rural production investment	农林牧渔固定资产投资 Fixed asset investment in the agriculture, forestry, animal husbandry and fisheries	+
数字产业发展 Digital industry development	农村生产数字化 Rural production digitalization	第一产业中数字经济增加值 Value added of digital economy in primary industry	+
	农村流通数字化 Digitalization of rural circulation	农村物流业务额 Rural logistics business revenue	+
	农村运营数字化 Digitalization of rural operations	农村电子商务销售额采购额 Rural e-commerce sales and purchase value	+
	农村数字产业创新基地 Rural digital industry innovation bases	淘宝村数量 Number of Taobao villages	+

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一级指标 Primary indicators	二级指标 Secondary indicators	三级指标 Tertiary indicators	属性 Attribute
抵抗能力水平 Absorptive capacity level	内在稳定性 Intrinsic stability	林地面积 Forest land area	+
		林业机械总动力 Total power of forestry machinery	+
		林业第一产业从业人员 Employees engaged in the primary industry of forestry	+
	产供鲁棒性 Supply stability	人均林业产值 Forestry output value per capita	+
		林产品价格指数 Forest product price index	?
		林业产值/林地面积 Forestry output value/forested land area	+
适应能力水平 Adaptive capacity level	可持续性 Sustainability	林业碳排放总量 Total amount of forestry carbon emissions	?
		林业受灾防治率 Forestry disaster control rate	+
		林业农药使用量 Forestry pesticide use amount	?
	可恢复性 Recoverability	林业碳汇总量 Total forestry carbon sinks	+
		森林覆盖率 Forest cover	+
		林业增加值增长率 Forestry value-added growth rate	+
变革能力水平 Transformative capacity level	多样协作性 Multi-collaboration	林业能源投资 Forestry energy investment	+
		林下经济产值 Understory economy output value	+
		林业旅游与休闲产业带动产值 Output value generated by forestry tourism and recreation industry	+
	科技进步性 Technological progressiveness	林业科研支出 Expenditures on forestry research and development	+
		林业人员素质 Education of forestry industry employee	+
		林业科技推广站数量 Forestry technology extension stations number	+

变量 Variables	观测值 Observations	均值 Mean value	标准差 Standard deviation	最小值 Minimum value	最大值 Maximum value
林业经济韧性 Forestry economic resilience	300	0.141	0.082	0.023	0.398
农村数字化发展水平 Rural digital development level	300	0.394	0.116	0.148	0.715
经济发展水平 Economic development level（million yuan per capita）	300	5.651	2.622	1.943	13.605
产业结构 Industrial structure (%)	300	0.431	0.087	0.188	0.575
城镇化水平 Urbanization level（%）	300	0.590	0.122	0.369	0.893
生态环境水平 Ecological environment level（%）	300	0.207	0.133	0.000	0.479
降水量 Quantity of rainfall/（mm?km^?2）	300	0.017	0.038	0.000	0.232

省（区、市） Provinces (autonomous region, municipalities)	2011		2015		2020
省（区、市） Provinces (autonomous region, municipalities)	综合指数 Comprehensive index	排名 Ranking	综合指数 Comprehensive index	排名 Ranking	综合指数 Comprehensive index	排名 Ranking
北京 Beijing	0.383	1	0.485	4	0.583	8
天津 Tianjin	0.261	10	0.374	16	0.444	22
河北 Hebei	0.266	8	0.421	9	0.550	10
山西 Shanxi	0.241	14	0.364	19	0.446	21
内蒙古Inner Mongolia	0.195	24	0.333	23	0.426	27
辽宁 Liaoning	0.268	7	0.416	11	0.453	20
吉林 Jilin	0.232	17	0.374	17	0.427	26
黑龙江 Heilongjiang	0.253	12	0.384	14	0.475	17
上海 Shanghai	0.358	3	0.416	10	0.505	12
江苏 Jiangsu	0.344	5	0.521	3	0.708	3
浙江 Zhejiang	0.359	2	0.522	2	0.751	1
安徽 Anhui	0.206	20	0.362	20	0.523	11
福建 Fujian	0.324	6	0.480	5	0.585	7
江西 Jiangxi	0.178	25	0.338	22	0.467	18
山东 Shandong	0.259	11	0.424	8	0.602	6
河南 Henan	0.262	9	0.443	6	0.649	4
湖北 Hubei	0.248	13	0.436	7	0.629	5
湖南 Hunan	0.195	23	0.374	18	0.496	14
广东 Guangdong	0.346	4	0.532	1	0.750	2
广西 Guangxi	0.204	21	0.376	15	0.501	13
海南 Hainan	0.156	27	0.285	30	0.368	30
重庆 Chongqing	0.203	22	0.328	25	0.458	19
四川 Sichuan	0.235	16	0.407	12	0.577	9
贵州 Guizhou	0.090	30	0.302	28	0.428	25
云南 Yunnan	0.155	28	0.317	27	0.490	15
陕西 Shaanxi	0.240	15	0.388	13	0.480	16
甘肃 Gansu	0.141	29	0.291	29	0.439	23
青海 Qinghai	0.162	26	0.331	24	0.398	28
宁夏 Ningxia	0.210	19	0.320	26	0.393	29
新疆 Xinjiang	0.214	18	0.355	21	0.438	24

变量 Variables	双向固定效应模型 Two-way fixed effects model
变量 Variables	（1）		（2）
农村数字化发展水平 Rural digital development level	0.478***	（0.129）	0.435***	（0.126）
经济发展水平 Economic development level			0.022***	（0.008）
产业结构水平 Industrial structure level			0.148*	（0.073）
城镇化水平 Urbanization level			0.304	（0.198）
生态环境水平 Ecological environment level			0.031	（0.056）
降雨量 Quantity of rainfall			0.544**	（0.235）
常数项 Constant	?0.048	（0.051）	?0.415***	（0.134）
年份 Year	√		√
省份 Province	√		√
豪斯曼检验 Hausman test	39.85***		47.25***
观测值 Observations	300		300
R²	0.942		0.954

变量 Variables	改变自变量测度方法Measurement method of independent variables changed	滞后一期 One period lagged	控制区域时间趋势项 Area and time trend controlled	剔除直辖市 Municipalities excluded
农村数字化发展水平	0.080***	0.382***	0.416***	0.422***
Rural digital development level	（0.024）	（0.115）	（0.130）	（0.125）
控制变量 Control variables	√	√	√	√
年份 Year	√	√	√	√
省份 Province	√	√	√	√
区域时间趋势项 Area time trend item	×	×	√	×
常数项 Constant	?0.311**	?0.462***	0.979**	?0.209
	（0.149）	（0.153）	（0.376）	（0.150）
观测值 Observations	300	270	300	260
R²	0.956	0.961	0.959	0.951

Can the Rural Digital Development Improve Forestry Economic Resilience: An Empirical Evidence Based on Panel Data of 30 Provinces

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变量 Variables	第一阶段 Stage I	第二阶段 Stage II
农村数字化发展水平		0.860***
Rural digital development level		（0.224）
工具变量	0.017***
Instrumental variable	（0.003）
常数项	?0.597***	?0.437***
Constant	（0.158）	（0.163）
控制变量 Control variables	√	√
年份 Year	√	√
省份 Province	√	√
Kleibergen-Paaprk LM	17.295 [0.000]
Kleibergen-Paaprk Wald F	28.014 [16.38]
观测值Observations	300

变量 Variables	资源配置效率 Resource allocation efficiency
变量 Variables	劳动力资源生产率 Labor resource productivity	土地资源生产率 Land resource productivity
农村数字化	0.775***	0.218***
Rural digital development level	（0.233）	（0.075）
控制变量 Control variables	√	√
年份 Year	√	√
省份 Province	√	√
常数项 Constant	?1.049*** （0.267）	?0.334** （0.145）
观测值 Observations	300	300
R²	0.915	0.959

变量 Variables	东部地区样本	中部地区样本	西部地区样本
变量 Variables	Eastern region sample	Central region sample	Western region sample
农村数字化发展水平	0.359**	0.638	0.222
Rural digital development level	（0.146）	（0.346）	（0.127）
控制变量 Control variables	√	√	√
年份 Year	√	√	√
省份 Province	√	√	√
常数项	?0.653***	?0.266	?0.270
Constant	（0.179）	（0.760）	（0.221）
观测值 Observations	120	80	110
R²	0.964	0.941	0.970

变量 Variables	0.10分位点 0.10 quantile	0.25分位点 0.25 quantile	0.50分位点 0.50 quantile	0.75分位点 0.75 quantile	0.90分位点 0.90 quantile
农村数字化发展水平	0.212	0.166**	0.406***	0.522***	0.522***
Rural digital development level	（0.166）	（0.077）	（0.014）	（0.004）	（0.005）
控制变量 Control variables	√	√	√	√	√
年份 Year	√	√	√	√	√
省份 Province	√	√	√	√	√
观测值 Observations	300	300	300	300	300

门槛变量 Threshold variable	门槛数量 Threshold number	F	P	抽样次数 Bootstrap time	临界值Critical value
门槛变量 Threshold variable	门槛数量 Threshold number	F	P	抽样次数 Bootstrap time	10%	5%	1%
农村数字化发展水平 Rural digital development level	1	39.03	0.024	1 000	24.500	32.796	46.426
	2	27.33	0.095	1 000	25.194	50.969	72.038
	3	20.22	0.254	1 000	33.539	44.386	69.418

门槛变量 Threshold variable	门槛模型 Threshold model	门槛值 Threshold value	95% 置信区间 95% confidence interval
农村数字化发展水平 Rural digital development level	双重门槛模型 Dual-threshold model	0.195	[0.177, 0.195]
农村数字化发展水平 Rural digital development level	双重门槛模型 Dual-threshold model	0.649	[0.295, 0.650]

变量Variables	林业经济韧性 Forestry economic resilience
农村数字化发展水平 $ \times {I(T}_{it}{\le \theta }_{1}) $	0.443***
Rural digital development level $ \times {I(T}_{it}{\le \theta }_{1}) $	（0.070）
农村数字化发展水平$ \times {I({\theta }_{1} < T}_{it}{ < \theta }_{2}) $	0.221***
Rural digital development level $ \times {I({\theta }_{1} < T}_{it}{ < \theta }_{2}) $	（0.047）
农村数字化发展水平$ \times {I(T}_{it}{\ge \theta }_{2}) $	0.295***
Rural digital development level $ \times {I(T}_{it}{\ge \theta }_{2}) $	（0.045）
控制变量 Control variables	Yes
年份Year	Yes
省份Province	Yes
常数项 Constant	?0.177***
	（0.055）
观测值 Observations	300

变量Variables	地理距离矩阵 Geographic distance matrix	邻接矩阵 Adjacent matrix	嵌套矩阵 Nested matrix
农村数字化发展水平	0.376***	0.197***	0.284***
Rural digital development level	（0.049）	（0.048）	（0.046）
空间权重矩阵元素× 农村数字化	0.895***	?0.146*	?0.196**
Spatial weight matrix elements× rural digital development level	（0.301）	（(0.085）	（0.089）
控制变量 Control variables	√	√	√
直接效应	0.362***	0.193***	0.280***
Direct effect	（0.048）	（0.049）	（0.050）
控制变量 Control variables	√	√	√
间接效应	0.456**	?0.125	?0.103
Indirect effect	（0.195）	（0.10）	（0.179）
控制变量 Control variables	√	√	√
总效应	0.818***	0.069	0.177
Total effect	（0.201）	（0.115）	（0.203）
控制变量 Control variables	√	√	√
观测值 Observations	300	300	300
ρ	0.514**	0.225***	0.493***
sigma2_e	0.000***	0.000***	0.000***

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农村数字化发展水平 Rural digital development level		林业经济韧性 Forestry economic resilience
年份 Year	莫兰指数 Moran’s I	年份 Year	莫兰指数 Moran’s I
2011	0.385***	2011	0.307***
2012	0.403***	2012	0.273***
2013	0.339***	2013	0.256***
2014	0.317***	2014	0.256**
2015	0.249**	2015	0.268***
2016	0.244**	2016	0.243**
2017	0.215**	2017	0.232**
2018	0.216**	2018	0.235**
2019	0.252**	2019	0.254**
2020	0.231**	2020	0.300***